| Summary: | Coal and gas outbursts are among the most severe disasters threatening the safety of coal mines around the world. They are dynamic phenomena characterized by large quantities of coal and gas ejected from working faces within a short time. Numerous researchers have conducted studies on outburst prediction, and a variety of indices have been developed to this end. However, these indices are usually empirical or based on local experience, and the accurate prediction of outbursts is not feasible due to the complicated mechanisms of outbursts. This study conducts outburst experiments using large-scale multifunctional equipment developed in the laboratory to develop a more robust outburst prediction method. In this study, the coal temperature during the outburst process was monitored using temperature sensors. The results show that the coal temperature decreased rapidly as the outburst progressed. Meanwhile, the coal temperature in locations far from the outburst mouth increased. The coal broken in the stress concentration state is the main factor causing the abnormal temperature rise. The discovery of these phenomena lays a theoretical foundation and provides an experimental basis for an effective outburst prediction method. An outburst prediction method based on monitoring temperature was proposed, and has a simpler and faster operation process and is not easily disturbed by coal mining activities. What is more, the critical values of coal temperature rises or temperature gradients can be flexibly adjusted according to the actual situations of different coal mines to predict outbursts more effectively and accurately.
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